magnitude and causes of bias among family caregivers rating alzheimer disease patients

Magnitude and Causes of Bias AmongFamily Caregivers Rating Alzheimer

Disease Patients

Richard Schulz, Ph.D., Thomas B. Cook, M.P.H., Scott R. Beach, Ph.D.,Jennifer H. Lingler, Ph.D., Lynn M. Martire, Ph.D., Joan K. Monin, Ph.D.,

Sara J. Czaja, Ph.D.

Received JanuaryUniversity (LMMand reprint requPittsburgh, 3343

� 2013 Amehttp://dx.d

14

Objective: Family caregivers generally underestimate the health and well-being of Alz-

heimer disease (AD) patientswhen compared to patients’ self-assessments. The goals of this

study were to identify caregiver, patient, and contextual factors associated with caregiver

rating bias. Methods: One hundred five patients with AD, along with their family

caregivers, were assessed twice by trained interviewers 1-year apart. In separate inter-

views, caregivers were asked to rate the quality of life and suffering of their patient

relative, and patients provided self-ratings using the same structured instruments.

Multivariate cross-sectional and longitudinal analyses were used to identify predictors of

caregiverepatient discrepancies. Results: Caregivers consistently reported significantly

higher levels of suffering and lower levels of quality of life than patients. Caregiver

psychological well-being and health status accounted for a substantial portion of the

difference in caregiver and patient ratings in both cross-sectional and longitudinal

analyses. Caregiver depression and burden were consistently positively associated with

the magnitude of caregiverepatient discrepancy, and caregiver health status was

negatively associated with the size of the discrepancy. Conclusions: Caregiver assess-

ments of dementia patients may determine the type and frequency of treatment received

by the patient, and caregivers’ ability to reliably detect change in patient status can play

a critical role in evaluating the efficacy of therapeutic interventions and pharmacologic

agents. Clinicians and researchers working with dementia patients who rely on care-

giver reports of patient status should be sensitive to the health and well-being of the

caregiver and recognize that caregiver assessments may be negatively biased when the

caregiver’s own well-being is compromised. (Am J Geriatr Psychiatry 2013; 21:14e25)

Key Words: Proxy ratings, caregiver, Alzheimer disease

roxy reports provided by family members are
Pfrequently used to characterize the health andwell-being of older individuals. Although secondary
6, 2011; revised July 6, 2011; accepted July 26, 2011. Fro), University Park, PA; Yale University (JKM), New Haests to Dr. Richard Schulz, Department of Psychiatry anForbes Avenue, Pittsburgh, PA 15260. e-mail: schulz@prican Association for Geriatric Psychiatryoi.org/10.1016/j.jagp.2012.10.002

reports of patient status may be better than having noinformation at all, it is important that we understandthe limitations of these reports. For patients with

m the University of Pittsburgh (RS, TBC, SRB, JHL), PA; Penn Stateven, CT; and University of Miami (SJC), FL. Send correspondenced University Center for Social and Urban Research, University ofitt.edu

Am J Geriatr Psychiatry 21:1, January 2013

mailto:[email protected]

http://dx.doi.org/10.1016/j.jagp.2012.10.002

Schulz et al.

dementia, family caregivers play critical roles incommunicating patient status information to health-care providers and advocating for patient care.1,2 Thevalidity and reliability of their assessment maydetermine the type and frequency of treatmentreceived by the patient, and their ability to reliablydetect change in patient status can play a critical rolein evaluating the efficacy of existing therapeuticinterventions and experimental pharmacologicagents. In as much as improving the quality of life ofdementia patients is a primary goal of treatment,having accurate assessments of patient status isessential.

The literature consistently shows that familyproxies report worse health-related quality of life andfunctioning for conditions such as stroke,3,4 cancer,5

dementia,6,7 and general health conditions8 whencompared to self-report measures from patients.Although several studies have shown that mild tomoderately impaired patients with dementia canprovide reliable self-report information about theirhealth and well-being,6,9e11 family members arefrequently viewed as the primary source of patientstatus information.12 Unfortunately, agreementbetween patient and caregiver reports of patientstatus is low to moderate at best,6,7,9e11,13 raisingquestions about the usefulness of family proxyreports as guides to patient treatment. Thus, treat-ment decisions based on proxy reports may not resultin maximal benefits from the patient’s perspective.

These findings beg the question, why do proxiesinfer worse health status than patients acknowledgeand how might this apparent bias be mitigated?Answering this question requires that we first identifyfactors that contribute to caregiver rating bias.Although not definitive, the literature suggestsa number of candidate variables including caregiverdepression,10,13 burden,7,10,13 patient depression,10

patient cognitive status,6,11,14 and the domain beingrated (e.g., subjective state versus observablebehavior).6,14 That is, larger discrepancies are reportedwhen either the patient or caregiver is depressed, thepatient is more cognitively impaired, the caregiver ismore burdened, and the domains being rated aresubjective states of the patient as opposed to observ-able behaviors such as physical functioning.

The present study sought to expand on thesefindings in several important ways. First, wecompare caregiver- and patient-rating disparities for


two widely used instruments, the Quality of Life inAD (QoL-AD) scale10 and the Dementia Quality ofLife (DEM-QoL) scale,15 to determine the level ofproxy rater bias. Second, we extend proxy-patientcomparisons to a recently validated measurementinstrument designed to assess patient suffering inthree domains: psychological, existential, and phys-ical suffering.16 This enables us to assess variations inbias in both subjectively experienced (psychologicaland existential suffering) and objectively observeddomains (physical suffering). Third, we systemati-cally explore multiple caregiver, patient, andcontextual factors associated with caregiver ratingbias to identify key factors that predict bias. Finally,in longitudinal analyses, we examine how changes incaregiver characteristics predict changes in caregiverbias. The latter analyses are unique in this literatureand are critical to developing causal models forunderstanding and addressing caregiver bias.

METHODS

Measures

Both caregivers and patients completed twoquality of life instruments, the QoL-AD scale10 andthe DEM-QoL scale15 and a recently validatedsuffering scale composed of three subscales assessingpsychological, existential, and physical suffering.16

The QoL-AD consists of 13 items assessing multipledimensions of quality of life (e.g., mood, energy,friends, ability to do things for fun) as either poor (1),fair (2), good (3), or excellent (4; range: 13e52; higherscores indicate higher quality of life). The DEM-QoLis a 28-item scale assessing multiple dimensions ofquality of life, including psychological status,memory, and daily activities. Respondents are askedto indicate how much they experienced each itemduring the last week (“a lot” ¼ 1; “quite a bit” ¼ 2; “alittle” ¼ 3; “not at all” ¼ 4; range: 28e112; higherscores indicate higher quality of life). Psychologicalsuffering was measured with a scale assessing thefrequency of 15 symptoms (e.g., confident, afraid,irritable, depressed, cheerful, hopeless, etc.) experi-enced during the last 7 days (not at all ¼ 0; a little [afew days, 1e3] ¼ 1; quite a bit [most days, 4e6] ¼ 2;very often [every day] ¼ 3; range: 0e45; high scoresindicate high levels of suffering). Physical suffering

15

Bias Among Family Caregivers Rating AD Patients

was measured with 9 items assessing symptoms suchas pain, nausea, shortness of breath, dry mouth, etc.,using the same response options as the psychologicalsuffering scale. We calculated an index score bycoding symptoms that occurred “quite a bit” or “veryoften” as 1 and all other responses as 0 (range: 0e7).Spiritual/existential suffering was measured with 9statements (I feel peaceful, My life has been a failure,I feel a sense of purpose in my life, Life is not worthliving anymore, etc.). Respondents are asked toindicate how true each statement has been for themduring the past 7 days (not at all ¼ 0, a little ¼ 1,somewhat ¼ 2, quite a bit ¼ 3, very much ¼ 4)yielding a score of 0 to 36 (high suffering). Positiveitems were reverse scored on all suffering scales.Patients were asked to rate themselves, and care-givers were asked to rate the patients on each of thesescales. Patients were also administered the Mini-Mental State Examination (MMSE), which assessescognitive functions of the patient (range: 0e30, highscores indicate high functioning)17 and the Short-Form 12 Question Health Survey18 which yieldstwo scores, one for mental health and one for phys-ical health (range: 0e100; high scores indicate betterhealth), and caregivers completed the Center forEpidemiologic Studies Depression (CES-D) scale19

(20 items; range: 0e60; high scores indicate greaterdepression), the Zarit Burden scale20 (12 items, range:0e48, high scores indicate greater burden), self-ratings of health, and provided information aboutdemographic characteristics of the household.

Sample and Procedure

Patients with Alzheimer disease (AD) and theircaregivers were recruited from the Alzheimer’sDisease Research Center at the University of Pitts-burgh and the local chapter of the Alzheimer’s Asso-ciation. Patients had to 1) be 50 years old or older; 2)have consensus-based diagnosis of probable orpossible AD or related dementia based on medical,behavioral, and cognitive function performance data;3) speak English; and 4) reside in the community withthe primary caregiver. Caregivers had to 1) be a familymember/partner (e.g., spouse, child, or fictive kin); 2)be 21 years of age or older; 3) provide a minimum of 3months of in-home care prior to recruitment; 4) speakEnglish; and 5) self-define as primary caregiver of thepatient. A total of 129 dyads were referred to the

16

study, and 121 met eligibility criteria. Of these, 16declined participation because of lack of interest in thestudy (n ¼ 10), caregiver was too busy (n ¼ 2), patienttoo ill (n ¼ 1), patient too depressed (n ¼ 1), patientrefused (n ¼ 1), or caregiver thought it would be tooupsetting for the patient (n ¼ 1), leaving a baselinesample of 105 dyads. A total of 92 caregiverscompleted the follow-up assessment 1 year later.Seven caregivers were lost due to the death of care-giver or patient, and six refused participation.Seventy-eight patients completed the follow-upassessments; of these, seven were lost due to deathof caregiver or patient, and 20were too ill or refused tocomplete the assessment. Patients who completed theassessment were further evaluated for competency toprovide reliable responses (see description of processlater in this article). A total of 79 dyads were able toreliably complete the baseline assessment and wereincluded in the baseline analysis; 54 dyads werejudged to provide reliable data at follow-up.

Data from caregivers and patients were collectedvia face-to-face interviews administered by a trainedinterviewer in the participant’s home. Caregivers andpatients were interviewed separately without thepresence of other individuals. Visual cue cards wereused to remind respondents of response options, andinterviewers were asked to assess the respondent’scomprehension by rating the ability of respondents toreliably answer questions and to ask follow-upquestions when responses were unclear or inconsis-tent. If the respondent was judged to be incapable ofcompleting the interview, the interviewer engagedthe respondent in an informal conversation beforeterminating the interview. On the basis of interviewerratings, MMSE scores, and analysis of responses tostructured questions, it was determined that personswith dementia scoring less than 16 on the MMSE(N ¼ 26) could not provide reliable responses atbaseline, and their data were, therefore, not used inthe analyses.

RESULTS

Demographics, Caregiver Relationships, andHousehold Characteristics

The demographic characteristics of the AD patients(N¼ 79) and their caregivers (N¼ 79) are presented in


TABLE 1. Caregiver and Patient Characteristics at Baseline

Caregivers(n [ 79)

Patients(n [ 79)

Age, mean (SD) 66.5 (11.0) 76.0 (8.5)Sex, N (%)

Female 64 (81) 27 (34)Male 15 (19) 52 (66)

Race, N (%)White 70 (89) 70 (89)Black 8 (10) 8 (10)Asian 1 (1) 1 (1)

Educational attainment, N (%)Less than high school 5 (6) 12 (15)High school 18 (23) 21 (27)Vocational or some college 20 (34) 19 (24)College degree 22 (28) 9 (11)Graduate degree 14 (18) 16 (20)

Caregiver employment status, N (%)Employed 17 (21)Homemaker 16 (20)Retired 36 (46)Unemployed 4 (5)

Total household income, N (%)<$20,000 18 (23)$20,000 to < $40,000 24 (30)$40,000 to < $60,000 16 (20)>$60,000 19 (24)Not reported 2 (3)

Years living in same household, N (%)<5 years 5 (6)5-10 years 6 (8)>10 years 68 (86)

RelationshipSpouse 58 (73)Non-spouse 21 (27)

Caregiver physical and mental healthstatusDepression (CES-D), mean (SD) 13.8 (11.2)Burden (ZBI), mean (SD) 14.8 (8.4)Self-rated healthPoor 4 (5)Fair 19 (24)Good 22 (28)Very Good 25 (32)Excellent 9 (11)

Patient physical and mental healthstatusMental health (SF-12) 44.1 (10.2)Physical health (SF-12) 47.2 (12.0)MMSE16-19 14 (18)20-24 33 (41)25-29 32 (41)Mean (SD) 23.1 (3.6)

Notes: SF-12: Short-Form 12 Question Health Survey, MentalHealth (MCS) and Physical Health (PCS) summary scores; ZBI:Zarit Burden Inventory.

Schulz et al.

Table 1. Patients’ ages ranged from55 to 95 (mean¼ 76,SD ¼ 8.5), and they were on average 10 years olderthan their caregivers (mean ¼ 67, SD ¼ 11.0; range:42e87). Caregivers were disproportionately female(84%), with 98% of male patients having a spouse(90%) or daughter caregiver (8%) and nearly half offemale patients cared for by a daughter (48%). Onaverage, patients had lower levels of educationalattainment than their caregivers, though this differ-ence was only observed among those patients whohad non-spouse caregivers. Overall, 42% of patientsreported a high school degree or less compared with29% of caregivers. The sample of patients is predomi-nately White (89%), with all patient and caregiverdyads concordant on self-reported race/ethnicity.Thus, caregiver demographic factors including age,sex, race, and educational attainment are confoundedwith patient characteristics.

As shown in Table 1, other demographic andhousehold factors such as the caregiver’s employmentstatus, total household income, and years living in thesame household are largely determined by the rela-tionship of the caregiver to the patient, with higherrates of current employment and higher incomesreported among non-spouse caregivers. Thougha majority (57%) of non-spouse caregivers reportedliving in the same household as the patient for greaterthan 10 years prior to the interview, 24% had lived inthe same household for less than 5 years. All spousecaregivers reported sharing the same household fora minimum of 5 years, with 97% having lived in thesame household for 10 years or more. Though thesehousehold factors may be potential sources ofdiscrepancy between caregiver and patient ratings,they are also largely mutually determined andconfounded. Thus, in subsequent multivariate anal-yses, total years living in the same household andhousehold income and race of the dyad are used tocapture the shared aspects of the household environ-ment, while relationship status was dropped as it wasredundant and collinear when included in multivar-iate models with caregiver sex, caregiver age, andyears living in the same household.

The analytic strategy was to first identify correlatesof systematic overrating of suffering and down-rating of quality of life by caregivers across a widerange of caregiver and patient characteristics as wellas shared factors such as household income and yearsliving together. To control for Type 1 error at this


stage of the analysis, we adopted a conservativestatistical significance criterion of p <0.01. The nextstep was to assess the relative importance of thesefactors both individually and as blocks of related

17


variables in explaining the residual differencebetween the caregiver and patient ratings in multiplelinear regression models. For each linear regressionmodel, the outcome variable is the caregiver’s ratingwith the patient’s rating entered at the first step. Afinal set of regression models assessed predictors ofdifferences in ratings of change in patient sufferingand quality of life.

Correlations and Concordance Among Measuresof Suffering and Quality of Life

The raw Pearson correlations between the caregiverandpatient ratings across thefive scalesmeasuring theseparate domains of patient suffering and quality oflife are presented in Table 2. Correlations betweencaregiver and patient ratings were generally mediumto low, with the highest observed correlation for theQoL-AD scale (r ¼ 0.354) and the lowest level ofagreement for the existential suffering scale (r¼ 0.279).These correlations suggest a similar pattern ofconcordance across the multiple measures of patientwell-being and are generally consistent with findingsof relatively low concordance among subjectivemeasures of patient status and quality of life.

Using paired t-tests, caregivers reported signifi-cantly higher levels of patient suffering than reportedby the patients across all three measures (Table 2).On average, caregivers also reported a significantlylower patient quality of life than did the patients onthe QoL-AD, but not for the DEM-QoL (Table 2).

Predictors of Caregiver Bias at Baseline

Overreporting of patient suffering and down-ratingof quality of life by the caregiver at baseline wassignificantly associated with measures of caregiverdepression across all scales except physical suffering(Table 3). Caregiver burden and physical health statuswere also strong and significant predictors of discor-dance for all scales except for physical suffering withthe additional exception that physical health statuswas not associated with psychological suffering.Amount of years living together was negativelyassociated with the discrepancy in physical suffering,and higher income was associated positively with thediscrepancy in quality of life as measured with theQoL-AD. Other demographic and household factorsdid not have statistically significant or consistentpatterns of relationship with caregiver bias across the

18

multiple scales using the conservative statisticalsignificance criterion of p <0.01.

After examining correlations among all predictorvariables (Table 4), we assessed associations amongindividual predictors and caregiver patient discrep-ancies using multivariate regression analyses. Theresults of these analyses are reported in Table 5.Because our sample size was relatively small andmany key predictor variables were highly correlated(e.g., caregiver burden, depression, and healthstatus), we also ran multivariate regression models inwhich we entered blocks of related variables to assessthe relative contribution of those blocks predictingdiscrepancies (Table 6). These analyses showed thatpsychosocial well-being and physical health status,including depression, burden, and general healthstatus, collectively explained nearly a quarter of thedifference between caregiver and patient ratings ofexistential suffering (DR2 ¼ 0.226) and quality of lifeusing the QoL-AD (DR2 ¼ 0.234). By comparison, thephysical and mental health status of patientsexplained less than 10% of the difference in ratingsacross all scales, suggesting that the degree of care-giver bias in measures of suffering and quality of lifeare not dependent on the absolute level of physical ormental health symptoms experienced by the patient.Caregiver demographic factors including age, sex,and educational attainment accounted for just 6% ofdifference in ratings of existential suffering and lessthan 3% of differences for all other scales. Patientdemographic factors were significantly associatedwith discordance in ratings of existential sufferingbut otherwise explained very little of the variabilityacross the other scales. Household income, yearsliving together, and race/ethnicity were not associ-ated with caregiver bias after adjustment for otherfactors and collectively accounted for less than 5% ofthe difference in ratings.

Overall, the full models containing both caregiverand patient demographics, physical and mentalhealth status variables, and shared household factorswere able to explain a substantial portion of thecaregiver bias in ratings of existential suffering(DR2 ¼ 0.444) and quality of life measured with theQoL-AD (DR2 ¼ 0.366). Multivariate modelsexplained less than one-third of the observed differ-ences in ratings of psychological suffering (DR2 ¼0.316), Dementia Quality of Life (DR2 ¼ 0.296), andphysical suffering (DR2 ¼ 0.208), though the latter


TABLE 3. Correlations Between Selected Caregiver and Patient Characteristics and Discrepancy in Scale Ratings of Patient’sSuffering and Quality of Lifea

Care Recipient Suffering MeasuresCare RecipientQuality of Life

Psychological Existential Physical QoL-AD DEM-QoL

Demographic factorsCaregiver

Age (years) �0.194 �0.069 �0.119 �0.098 0.148Sex (female) �0.051 0.063 �0.034 �0.124 0.004Education �0.094 �0.111 �0.300 0.138 0.079

PatientAge (years) �0.108 �0.098 .124 �0.027 0.175Sex (female) 0.144 0.104 .109 0.142 �0.039Education �0.203 �0.249 �0.269 0.094 0.123

Physical and mental health statusCaregiver

Depression (CES-D) 0.435* 0.452* 0.236 �0.337* �0.328*Burden 0.400* 0.390* 0.196 �0.400* �0.293*Health status �0.279 �0.346* �0.076 0.300* 0.292*

PatientMMSE �0.127 0.015 0.087 �0.053 0.144Physical health (SF-12) �0.027 0.042 �0.155 0.150 �0.064Mental health (SF-12) �0.081 0.044 �0.059 �0.064 �0.051

Household or shared factorsRace (non-White) 0.068 �0.036 �0.064 �0.005 0.122Non-spouse caregiver 0.168 0.121 0.195 0.043 �0.108Years living together �0.202 �0.095 �0.235* 0.024 0.116Household income �0.124 �0.127 �0.165 0.270* 0.120

Notes: SF-12: Short-Form 12 Question Health Survey, Mental Health (MCS) and Physical Health (PCS) summary scores.*p <0.01.aPearson correlations (df ¼ 77) are between the residual of the caregiver rating regressed on the patient rating and selected factors.

TABLE 2. Suffering and Quality of Life Measures: Means, Standard Deviations, and Measures of Concordance Between Caregiversand Patients

Caregiver(n [ 79)

Patient(n [ 79)

Paired Differencea

Caregiver L Care Recipient Correlationb r

Suffering measuresPsychological 11.3 (6.5) 7.3 (6.6) 4.0 (7.5)* 0.345*Existential/spiritual 11.0 (6.1) 6.4 (6.1) 4.6 (7.4)* 0.279Physical (index) 2.0 (1.5) 1.0 (1.3) 1.0 (1.7)* 0.288*

Quality-of-life measuresQoL-AD 30.0 (5.3) 34.6 (4.9) �4.6 (5.8)* 0.354*DEM-QoL 92.9 (13.4) 91.7 (11.2) 1.2 (14.5) 0.315*

Notes: *p <0.01.aPaired t test (df ¼ 78) comparing differences in raw scales scores between caregiver and patient rating.bRaw Pearson correlation (df ¼ 77) between caregiver and patient ratings for each scale.

Schulz et al.

two measures had relatively low levels of discor-dance, leaving less to be explained.

Predictors of Caregiver Bias in Assessing Change

Agreement between caregiver and patient ratings ofchange between 1-year follow-up and baseline scores(Table 7) were also generally poor, although correla-tions for both psychological suffering (r ¼ 0.340) and


the QoL-AD (r ¼ 0.381) were moderate. Thoughaverage changes in ratings of the DEM-QoL weresimilar between caregivers (mean D ¼ 2.2, SD ¼ 10.9)and patients (mean D ¼ 2.1, SD ¼ 8.5), the correlationbetween pairs of ratings of change is very poor(r ¼ 0.004). Patients generally reported higher exis-tential suffering at follow-up than at baseline(meanD¼ 1.6, SD¼ 3.2), but this mean difference wasnot captured in caregiver ratings (mean D ¼ �0.06,

19

TABLE 4. Correlation Matrix of Selected Covariates and Predictors of Measures of Patient Suffering and Quality of Lifea

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

Demographic factorsCaregiver

1 Age 1 �0.039 �0.050 0.175 �0.291* 0.235 �0.210 �0.291* �0.050 0.001 0.094 0.178 �0.252 �0.703* 0.742* �0.1002 Sex (Female) �0.039 1 0.071 0.120 �0.604* 0.009 0.176 0.253 �0.150 0.180 0.013 0.336* �0.01 0 �0.078 �0.0903 Education �0.046 0.071 1 �0.020 �0.050 0.574* �0.170 0.240 0.189 �0.040 0.010 0.110 �0.02 0.036 �0.075 0.583*

Patient4 Age 0.200 0.120 �0.020 1 0.204 �0.192 �0.070 0.059 �0.040 0.042 �0.119 0.089 0.118 0.397* �0.008 �0.0105 Sex (female) �0.291* �0.604* �0.050 0.204 1 �0.327* �0.030 0.013 �0.010 �0.210 �0.072 �0.327* 0.207 0.533* �0.179 0.0836 Education 0.235 0.009 0.574* �0.190 �0.327* 1 �0.100 0.110 0.177 0.010 0.040 0.034 �0.03 �0.379* 0.082 0.341*

Physical and mentalhealth statusCaregiver

7 Depression (CES-D) �0.200 0.176 �0.170 �0.070 �0.030 �0.095 1 0.606* �0.507* 0.102 �0.086 0.051 �0.18 0.054 �0.186 �0.1808 Burden �0.291* 0.253 0.240 0.059 0.013 0.110 0.606* 1 �0.231 0.117 �0.089 �0.120 �0.03 0.225 �0.347* 0.0379 Health status �0.100 �0.148 0.189 �0.040 �0.010 0.177 �0.507* �0.231 1 0.003 0.073 0.044 �0.07 0.02 �0.066 0.267

Patient10 MMSE 0.000 0.180 �0.040 0.042 �0.210 0.010 0.102 0.117 0.003 1 �0.072 0.126 �0.17 �0.130 �0.090 0.00311 Physical health

(SF-12)0.100 0.013 0.010 �0.120 �0.070 0.040 �0.090 �0.089 0.073 �0.070 1 0.054 �0.15 �0.110 0.091 �0.010

12 Mental health 0.200 0.336* 0.110 0.089 �0.327* 0.034 0.051 �0.122 0.044 0.126 0.054 1 �0.385* �0.100 0.133 0.138Household or sharedfactors

13 Race (non-white) �0.252 �0.010 �0.020 0.118 0.207 �0.032 �0.180 �0.031 �0.070 �0.170 �0.149 �0.385* 1 0.288 �0.356* �0.28814 Non-spouse �0.703* �0.001 0.036 0.397* 0.533* �0.379* 0.054 0.225 0.020 �0.130 �0.106 �0.1 0.288 1 �0.627* 0.10715 Years of caregiving 0.742* �0.078 �0.080 �0.010 �0.180 0.082 �0.190 �0.347* �0.070 �0.090 0.091 0.133 �0.356* �0.627* 1 �0.1216 Household income �0.100 �0.090 0.583* �0.010 0.083 0.341* �0.180 0.037 0.267 0.003 �0.012 0.138 �0.288 0.107 �0.119 1

Notes: SF-12: Short-Form 12 Question Health Survey, Mental Health (MCS) and Physical Health (PCS) summary scores.*p <0.01 level.aPearson correlations (df ¼ 77) between pairs of measures.

20Am

JGeriatr

Psych

iatry21:1,

January

2013

BiasAmongFamily

Caregivers

Ratin

gAD

Patie

nts

TABLE 5. Multiple Regression Models Assessing Sources of Discrepancy Between Caregiver and Patient Ratings of Patient’s Sufferingand Quality of Lifea



Demographic factors beta beta beta beta beta

CaregiverAge (years) 0.155 0.341* 0.114 �0.275 0.021Sex (female) �0.094 0.085 �0.100 0.070 0.137Education 0.005 0.051 �0.269 0.019 �0.012

PatientAge (years) �0.168 �0.295* 0.130 0.021 0.157Sex (female) 0.051 0.232 �0.015 0.141 0.063Education �0.186 �0.311* �0.051 0.120 0.110


Depression (CES-D) 0.226 0.355 0.020 �0.283 0.012Burden 0.328* 0.374* 0.162 �0.530** �0.243Health status �0.207 �0.414* 0.028 0.377* 0.079

PatientMMSE �0.140 0.008 �0.018 0.014 0.205Physical health (SF-12) 0.159 0.360* �0.031 �0.353* 0.240Mental health (SF-12) 0.049 0.288 0.012 �0.476* �0.021

Household or shared factorsRace (non-White) 0.111 0.100 �0.194 �0.080 0.247Years living together �0.134 �0.125 �0.326 0.129 0.183Household income �0.020 0.002 �0.046 0.177 0.115

Notes: SF-12: Short-Form 12 Question Health Survey, Mental Health (MCS) and Physical Health (PCS) summary scores.*p <0.05, **p <0.01.aStandardized regression coefficients (beta) predicting discrepancy in score rating (the residual variance between caregiver and patient

ratings). Tests of significance are based on t tests in multiple regression model (df ¼ 63).

Schulz et al.

SD ¼ 4.3). On average, both caregivers and patientsreported little change in the average levels of physicalsuffering for the study cohort.

As was the case for baseline measures, the mostimportant predictors of discrepancy between care-giver and patient ratings of change were changes inmeasures of caregiver physical and mental healthstatus (Table 8). Of these caregiver factors, changes incaregiver depression was the most important forpredicting bias in ratings of change in patientpsychological suffering and QoL-AD, while changesin the caregiver’s health status were relatively moreimportant in predicting bias in assessment of changeof existential suffering and the DEM-QoL. Thus, notonly do caregivers with higher levels of depressionand self-reported burden and poorer physical healthtend to overrate patient suffering and down-ratequality of life at baseline, changes in their ownmental and physical health status may additionallybias measures of change in patient suffering andquality of life. Changes in the physical and mentalhealth status of the caregiver accounted for


a significant portion of the discrepancy betweencaregiver and patient ratings of psychologicalsuffering (R2 ¼ 0.185) and QoL-AD (R2 ¼ 0.153)where the outcome is the residual between caregiverand patient ratings of change. Though not statisti-cally significant, changes in caregiver well-being alsoexplained the largest proportion of the discrepancyfor existential suffering (R2 ¼ 0.096) and DEM-QoL(R2 ¼ 0.111) among the groups of variablesmeasured. The bias related to caregiver psychologicaland physical well-being detected at baseline is,therefore, not a constant that can be simply sub-tracted out of the equation in subsequent ratings.Because the most important sources of bias are notfixed but may change over time, the ability to reliablyassess changes in patient status may be undermined.

DISCUSSION

Concordance between caregiver and patientratings of patient suffering and quality of life was

21

TABLE 6. Summary of Multiple Regression Models Assessing Sources of Discrepancy Between Caregiver and Patient Ratings ofPatient’s Suffering and Quality of Life



DR2 DR2 DR2 DR2 DR2

Demographic factorsa

Caregiver 0.025 0.063 0.029 0.029 0.007Patient 0.046 0.107 ** 0.026 0.014 0.039

Physical and mental health statusCaregiverb 0.112* 0.226** 0.015 0.234** 0.047Patientc 0.022 0.062 0.003 0.066 0.018

Household or shared factorsd 0.016 0.025 0.053 0.019 0.029Full model, all factorse 0.316* 0.444** 0.208 0.366** 0.296*

Notes: *p <.05, **p <0.01.Results showing DR2 and p values from F-tests to assess the relative contributions of blocks of related variables in a multiple-regression

model predicting discrepancy in score rating (the residual variance between caregiver and patient ratings). All DR2 tests (df1 ¼ 3,df2 ¼ 63) for blocks of related variables and for the full model were evaluated when entered into the model at the final step, adjusted for allother variables. Blocks of variables were as follows:

aTwo blocks, one for caregiver demographics (age (continuous); sex (indicator); educational attainment (ordinal)) and one for patientdemographics (age (continuous), sex (indicator), educational attainment (ordinal)).

bBlock includes three variables measuring caregiver mental and physical health status at the time of interview: caregiver depression score(CES-D); caregiver burden score; caregiver general health status score.

cBlock includes three variables measuring patient’s mental and physical health status: Patient’s MMSE score; SF-12 physical healthsummary score; SF-12 mental health summary score.

dBlock includes total household income (ordinal); years of living together (continuous); race/ethnicity (indicator). Non-spouse status wasco-linear with total years living together and was removed from the model.

eTest for full model based on F-test (df1 ¼ 15, df2 ¼ 63) evaluating the contribution of all variables above in explanation of residual ofcaregiver rating regressed on patient rating.


small to moderate. With the exception of the DEM-QoL, caregivers consistently reported higher levels ofsuffering and lower levels of quality of life than re-ported by patients. These differences were large andstatistically significant. Multivariate analyses furthershowed that the caregiver’s own physical andpsychological well-being accounted for a substantialportion of this difference between caregiver andpatient ratings. Caregiver depression and burdenwere consistently positively associated with themagnitude of caregiverepatient discrepancy, and

TABLE 7. Mean Change and Measures of Concordance of Change in

Caregiver (n [ 54) Patient (n [ 54) P

Suffering measuresPsychological 0.45 (5.3) 1.25 (5.2)Existential/Spiritual �0.06 (4.3) 1.57 (3.2)Physical (Index) 0.11 (1.5) �0.15 (1.1)

Quality of life measuresQoL-AD �0.76 (4.2) �1.06 (4.3)DEM-QoL 2.15 (10.9) 2.08 (8.5)

Notes: *p <0.05, **p <0.01.aPaired t test (df ¼ 53) comparing differences in raw change scores bebRaw Pearson correlation (df ¼ 52) between change in caregiver and p

22

caregiver health status was negatively associatedwith the size of the discrepancy.

Agreement between caregiver and patient ratingsof change between baseline and 1-year follow-upscores were also generally poor, although correla-tions for two scales, psychological suffering and QoL-AD, were moderate. As was the case for baselinemeasures, the most important predictors of discrep-ancy between caregiver and patient ratings of changewere changes in measures of caregiver physical andmental health status. Of these caregiver factors,

Suffering and Quality of Life Measures (N [ 54)

aired Differencea Caregiver L Care Recipient Correlationb r

�0.81 (6.1) 0.340*�1.63 (5.7) �0.1050.26 (1.7) 0.179

0.30 (4.6) 0.381**0.07 (13.8) 0.004

tween caregiver and patient rating.atient ratings for each scale.


TABLE 8. Summary of Multiple Regression Models Assessing Sources of Discrepancy Between Changes in Caregiver Ratings andChanges in Patient Ratings of Patient’s Suffering and Quality of Life (N [ 54)

DCare Recipient Suffering Measures(T2 L T1)

DCare Recipient Quality ofLife (T2 L T1)


DR2 DR2 DR2 DR2 DR2

Demographic factorsa

Caregiver 0.011 0.008 0.043 0.065 0.003Patient 0.052 0.090 0.046 0.123* 0.003


Baselineb 0.013 0.049 0.085 0.076 0.040Changec 0.185* 0.096 0.019 0.153* 0.111

PatientBaselined 0.040 0.124 0.041 0.149* 0.049Changee (MMSE only) 0.015 0.005 0.005 0.002 0.077

Household or shared factorsf 0.078 0.082 0.041 0.099 0.011Full model, all factorsg 0.469 0.535 0.326 0.648** 0.398

Notes: *p <0.05, **p <0.01.Results showing DR2 and corresponding F-tests to assess the relative contributions of blocks of related variables in a multiple-regression

model predicting discrepancy in assessments of change (the residual variance between caregiver and patient ratings of change). All F-tests forblocks of related variables and for the full model were evaluated when entered into the model at the final step, adjusted for all other variables.Blocks of variables were as follows:

aTwo blocks, one for caregiver demographics (age [continuous]; sex [indicator]; educational attainment [ordinal]) and one for patientdemographics (age [continuous], sex [indicator], educational attainment [ordinal] [F, df1 ¼ 3, df2 ¼ 34]).

bBlock includes three variables measuring caregiver mental and physical health status at the time of the baseline interview: Caregiverdepression score (CES-D); caregiver burden score; caregiver general health status score (F, df1 ¼ 3, df2 ¼ 34).

cBlock includes the change in ratings of caregiver depression (CES-D), caregiver burden and caregiver general health status score (F, df1 ¼ 3,df2 ¼ 34).

dBlock includes three variables measuring patient’s mental and physical health status at baseline: Patient’s MMSE score; SF-12 physicalhealth summary score; SF-12 mental health summary score (F, df1 ¼ 3, df2 ¼ 34).

eBlock includes change in patient’s MMSE score only, SF-12 scores only captured at baseline (F, df1 ¼ 1, df2 ¼ 34).fBlock includes total household income (ordinal); years of living together (continuous); race/ethnicity (indicator). Non-spouse status was

co-linear with total years living together and was removed from the model (F, df1 ¼ 3, df2 ¼ 34).gFull model evaluates the contribution of all variables above in explanation of residual of caregiver rating regressed on patient rating

(F, df1 ¼ 19, df2 ¼ 34).

Schulz et al.

changes in caregiver depression were most importantfor predicting negative bias in ratings of change.

These findings both replicate and extend priorresearch in this area and have important implicationsfor both care of the patient and for clinical trials indementia.21 Because of patient cognitive impairment,the caregiver is often the primary source of infor-mation on patient health and well-being in healthcareencounters. Caregivers with high levels of depressivesymptoms and burden are likely to exaggeratenegative aspects of patient status, resulting inpotentially nonoptimal and inappropriate medicalinterventions for the patient. For example,a depressed caregiver may exaggerate depressivesymptoms in the patient and advocate unnecessarytreatment for depression. Clinicians treatingdementia patients who rely on caregiver reports ofpatient status should be sensitive to the health and


well-being of the caregiver and recognize that care-giver assessments may be negatively biased when thecaregiver’s own well-being is compromised.

Our findings are particularly relevant to outcomesassessment in clinical trials involving dementiapatients. The Food and Drug Administration requiresthat the global impression of a clinician serve asa primary outcome in clinical trials in dementia. Toaddress this requirement, researchers frequently usethe clinician’s interview-based impression of changewith the caregiver input scale (CIBIC-plus).22 Thisinstrument uses information obtained during anindependent clinical interview to assess diseaseseverity and progression in multiple domains. Ablinded clinician conducts interviews with the patientand caregiver. Our findings suggest that caregiversmay be a potential source of bias in these ratings,resulting in an underestimate of treatment efficacy.

23


Clinicians who identify discrepancies between care-giver and patient during CIBIC administrationshould consider the caregivers’ depressive statuswhen interpreting these discrepancies.

Caregiver bias does not account for all of thediscrepancy between caregiver and patient ratings ofpatient status. This begs the question, what elsemight account for these relatively large differences?One possible explanation concerns the differentperspectives that patients and caregivers bring to thedisease. Patients experiencing the disease may havea vested interest in downplaying its impact on themas a means for coping with it or in an attempt toreduce the burden on the caregiver. In addition,patients may find the reality of the disease to be lessnegative than their expectations about it. On thecontrary, it would be socially inappropriate forcaregivers to downplay patient symptoms, andcaregivers are subject to the generally negativemedia-based characterizations of the disease becausethey have no first-hand experience with it. It has alsobeen suggested that AD patients’ lack of insight maycontribute to more positive self-assessments.21

Limitations

Given the large number of statistical tests carriedout and the relatively small sample available for thisstudy, the results should be viewed cautiouslybecause of possible Type I error. Replication witha larger sample is warranted. Our findings also pointto a number of unanswered questions. It is note-worthy that we did not find significant caregivere

24

patient discrepancies on the DEM-QoL, which maybe due to the fact that this scale contains numerousitems that rely on behavioral observation of thepatients (e.g., keeps him/herself clean; looks afterhis/her finances) as opposed to inferring internalstates. It would be useful to explore this distinctionmore systematically in future studies. Given therelatively advanced age of our caregivers, it ispossible that they too might have suffered from mildcognitive impairment, which affected their judgment.Future studies should formally assess the cognitivefunction of both caregivers and patients. Similarly,having caregivers and patients rate both themselvesand their respective relative/friend would showwhether these disparities are a general phenomenonregardless of which role one occupies. Answeringthese questions and obtaining a more fine-grainedunderstanding of the causes and consequences ofcaregiver rater bias should receive high priority.Nevertheless, the growing literature in this areastrongly suggests that caution be advised in makingclinical decisions based on caregiver reports.

Preparation of this manuscript was in part supportedby grants from the Alzheimer’s Association (IIRG-07-59784), National Institute of Nursing Research(NR08272, 09573), National Institute on Aging (P50AG05133, AG015321, and AG026010), National Insti-tute of Mental Health (MH071944), National Heart, Lungand Blood Institute (HL076852 and HL076858), andNational Science Foundation (EEEC-0540865).

The authors have no disclosures to report.

References

1. Schmidt KL, Lingler JH, Schulz R: Verbal communication amongAlzheimer’s disease patients, their caregivers, and primary carephysicians during primary care office visits. Patient Educ Couns2009; 77:197e209

2. Hunsaker AE, Schmidt KL, Lingler JH: Discussing dementia-relatedbehaviors during medical visits for people with Alzheimer’sdisease. Am J Alzheimer’s Dis Other Demen 2010; 25:248e254

3. Williams LS, Bakas T, Brizendine E, et al: How valid are familyproxy assessments of stroke patients’ health-related quality of life?Stroke 2006; 37:2081e2085

4. Sneeuw KC, Aaronson NK, de Haan RJ, et al: Assessing quality oflife after stroke. The value and limitations of proxy ratings. Stroke1997; 28:1541e1549

5. Farrow DC, Samet JM: Comparability of information provided byelderly cancer patients and surrogates regarding health andfunctional status, social network, and life events. Epidemiology1990; 1:370e376

6. Novella JL, Boyer F, Jochum C, et al: Health status in patients withAlzheimer’s disease: an investigation of inter-rater agreement.Qual Life Res 2006; 15:811e819

7. Sands LP, Ferreira P, Stewart AL, et al: What explains differ-ences between dementia patients’ and their caregivers’ ratingsof patients’ quality of life? Am J Geriatr Psychiatry 2004; 12:272e280

8. Magaziner J, Zimmerman SI, Gruber-Baldini AL, et al: Proxyreporting in five areas of functional status: comparison with self-reports and observations of performance. Am J Epidemiol 1997;146:418e428

9. Ready RE, Ott BR, Grace J: Patient versus informant perspectivesof Quality of Life in Mild Cognitive Impairment and Alzheimer’sdisease. Int J Geriatr Psychiatry 2004; 19:256e265

10. Logsdon RG, Gibbons LE, McCurry SM, et al: Assessing quality oflife in older adults with cognitive impairment. Psychosom Med2002; 64:510e519


Schulz et al.

11. Novella JL, Jochum C, Jolly D, et al: Agreement between patients’and proxies’ reports of quality of life in Alzheimer’s disease. QualLife Res 2001; 10:443e452

12. Adams WL, McIlvain HE, Geske JA, et al: Physicians’ perspectiveson caring for cognitively impaired elders. Gerontologist 2005; 45:231e239

13. Karlawish JH, Casarett D, Klocinski J, et al: The relationshipbetween caregivers’ global ratings of Alzheimer’s diseasepatients’ quality of life, disease severity, and the caregivingexperience. J Am Geriatr Soc 2001; 49:1066e1070

14. Loewenstein DA, Argüelles S, Bravo M, et al: Caregivers’ judg-ments of the functional abilities of the Alzheimer’s diseasepatient: a comparison of proxy reports and objective measures.J Gerontol B Psychol Sci Soc Sci 2001; 56:P78eP84

15. Smith SC, Lamping DL, Banerjee S, et al: Development of a newmeasure of health-related quality of life for people with dementia:DEMQOL. Psychol Med 2007; 37:737e746

16. Schulz R, Monin JK, Czaja SJ, et al: Measuring the experience andperception of suffering. Gerontologist 2010; 50:774e784


17. Folstein MF, Folstein SE, McHugh PR: “Mini-mental state”. Apractical method for grading the cognitive state of patients forthe clinician. J Psychiatr Res 1975; 12:189e198

18. Ware J Jr, Kosinski M, Keller SD: A 12-Item Short-Form HealthSurvey: construction of scales and preliminary tests of reliabilityand validity. Med Care 1996; 34:220e233

19. Radloff LS: The CES-D Scale: A self-report depression scale forresearch in the general population. Appl Psychol Meas 1977; 1:385e401

20. H�ebert R, Bravo G, Pr�eville M: Reliability, validity and referencevalues of the Zarit Burden Interview for assessing informal care-givers of community-dwelling older persons with dementia. Can JAging 2000; 19:494e507

21. Burke WJ, Roccaforte WH, Wengel SP, et al: Disagreement in thereporting of depressive symptoms between patients withdementia of the Alzheimer type and their collateral sources. Am JGeriatr Psychiatry 1998; 6:308e319

22. Reisberg B, Ferris SH: CIBIC-Plus Interview Guide. East Hanover,NJ, San doz Pharmaceuticals Corporation, 1994

25

magnitude and causes of bias among family caregivers rating alzheimer disease patients

Documents